Umm. 0:20 Steve Blank is not a billionaire. He’s not one in 2024. Pretty sure he wasnt one in 2017.

That covered a lot of ground :-)

Just curious if this would work with unknown or untrained words. That'd be an interesting challenge.

Nice.

smart

very nice walk through. I have a follow up question. If you want to apply the resulting model to a new dataset with several rows, how would you go about it?

so you don't actually use the tfidf corpus in the lda model?

I've gotten no words to thank you sir. Had been stuck on the validation loop over a week, but you made the same really easy... Thank you so much, again.

exactly what I was looking for--thank you!

Please increase video quality

can you share the link of the notebook in the video description !

Excellent Video using nice and Simple Example

Hi there, Thank you a lot, How can I run iOs simulator in windows 10? I have some problems in access API key. I cannot choose a team.

Awesome

How do i give names for the topic if i already have names for the topics. Like if i have data separatly without labels and topic names separatly

Great info and super helpful. A recommendation is to ensure that you don't cover the white board when presenting. Thanks for the great video~!

Excellent!

Make this video in hindi

Great were do I get that ViewModelBase file? Is it auto generated?

Best explanation I've seen so far. Thanks!

Hey Carlos I love your videos. Is there an email or cell where I can reach you? Thanks!

Hey Carlos. I love your videos. Do you have an email or cell where I can reach you?

what about running this code?

nice

Great session.

hi. we dont need to see trainin acuray after training?

Literally coming into this situation now. Thank you for sharing your story/info.

how do i just load the model next time when i want to run new images instead of training the model everytime?

How is the free course taken? Is it enough just to access the Google drive folder?

Very helpful video! Good balance between understanding the fundamentals and the code.

You dont even know how much you helped me!

Very good content, but it's sad that you are talking about AI and you don't use simple tech like green screen

excellent!!!! thank you for your clearly explain!

I love your explanation! Very straightforward! Love that you also keep the documentation nearby and explaining the little side things! Thank you!

I hope you'll dig further into specific examples and benefits in the future. Thanks.

easy to understand, thank you !!

I really appreciate it! Thank you, Carlos!

The github repository is corrupted

Good video. One tip might be to zoom in a bit because people may watch these on tv screen.

The same tutorial was provided in 2018 by Susan Li on her medium article Neural Machine Translation with Python. If you did use it please reference it next time.

From the code, at around 13:29, you have the following code. self.lstm = nn.lstm(len(self.chars), n_hidden.......) Can anyone explain me how many lstm nodes are created in the first layer? Can anyone explain me how input is sent to the first lstm layer? pls help me. I am stuck with this for more than 2 days.

--------------------------------------------------------------------------- It's working okay at first but now I'm getting error.Help me out please!!! NameError Traceback (most recent call last) <ipython-input-17-386dc3f680ce> in <module>() 50 model.train() 51 ---> 52 train_classifier() <ipython-input-17-386dc3f680ce> in train_classifier() 19 running_loss = 0 20 ---> 21 for images, labels in iter(train_loader): 22 23 steps += 1 NameError: name 'train_loader' is not defined

Really nice tutorial

May my gratitude make your day Mr. Carlos. Thanks a million. Thank you Man

great content, thanks a lot

Great video this is awesome!

may I ask what the assert dx_dy==0is for??

Cool tutorial! 1 way to improve your channel would be if you shared the code on the github.. The links that you put into description tend to disappear after some time. For example currently linked link to tensorflow site returns to 404 error already (after just 1 year after the video was posted). Github would also allow us to follow up the vides together with you :) Again, thank you for the effort and great video!

Hello! Great video! I have one question. How can i get the predictions of an unlabeled test set? (All test images, of custom dataset, are in the same folder and there are no labels. I need to get predictions for kaggle competition). Thank you in advance!

This has to be one of the best videos teaching about MVVM. You got a new subscriber ;)